Prediction and categorization of fabric drapability for 3D garment virtualization
International Journal of Clothing Science and Technology
ISSN: 0955-6222
Article publication date: 2 March 2020
Issue publication date: 15 July 2020
Abstract
Purpose
This study aims to create a classification system enabling users of 3D virtualization software to intuitively perceive the drapability of fabrics.
Design/methodology/approach
1,001 fabrics were used, and thickness, bending property, and tensile strength were identified as main mechanical properties influencing drapability; they have been set as independent variables in the model established to predict drape coefficient.
Findings
A system to classify fabrics into eight groups by drapability was suggested by a cluster analysis, and a multinomial logistic regression analysis was used to set a model that allows users to predict which group a fabric belongs to from its mechanical properties.
Originality/value
This paper provided basic materials for the construction of a virtual clothing simulation system, which is believed to contribute to cost and time savings in decision-making by reducing the number of trials and errors required by the conventional approach.
Keywords
Acknowledgements
This work was supported by the Ewha Womans University Research Grant of 2018 and by the Korea Textile Trade Association. We also appreciated the cooperation of CLO Virtual Fashion LLC.
Citation
Kim, J., Kim, Y.J., Shim, M., Jun, Y. and Yun, C. (2020), "Prediction and categorization of fabric drapability for 3D garment virtualization", International Journal of Clothing Science and Technology, Vol. 32 No. 4, pp. 523-535. https://doi.org/10.1108/IJCST-08-2019-0126
Publisher
:Emerald Publishing Limited
Copyright © 2020, Emerald Publishing Limited